On 08/21/2010 08:08 PM, Nick Torenvliet wrote: > Hi all, > > I'm trying to do a simple curve fit and coming up with some interesting > results I would like to get comment on. > So as shown below, tsR is my explanatory and response is... well... my > response. > > This same data in gnumeric gets fitted with the curve "response=10078.4 + > 1358.67 * ln (explanatory - 2009.07) > > So I'm using nls with the start values supplied by gnumeric. > > in "First Time Through" I'm very close to the values gnumeric found, I get > NaNs and Infinities. > > In "Second Time Through" I use the "exact" values given by gnumeric... and > it all come together fine. > > The difference between start value in First and Second time through is > practically insignificant and gnumeric was able to fit this without effort. > > At this rate R is basically useless to me -- what can I change here to set R > up better for this non-linear fit? > > What a shame... such a beautiful curve :-)
Hmm, nls is known to be somewhat finicky in the convergence department. Sometimes it works better with the "port" algorithm, but in this case, I think the culprit is pretty clear: Your "C" parameter is precariously close to the smallest value of tsR so the fitting algorithm will very easily walk into no-no territory. You could try helping the algorithm byt changing the log term to log(pmax(tsR-C,.001)). (Some may also question whether you really believe that the function should shoot off to minus infinity just to the left of your data...) A little piece of advice: If you want people to actually try things with the data, it would be helpful if you gave them using dput(), print() output can be tricky to read back in. -pd > > > **********************Data******************************* >> response > [1] 7062.93 7608.92 8168.12 8500.33 8447.00 9171.61 9496.28 9712.28 > [9] 9712.73 10344.84 10428.05 10067.33 10325.26 10856.63 11008.61 10136.63 > [17] 9774.02 10465.94 10319.95 > >> tsR > [1] 2009.167 2009.250 2009.333 2009.417 2009.500 2009.583 2009.667 2009.750 > [9] 2009.833 2009.917 2010.000 2010.083 2010.167 2010.250 2010.333 2010.417 > [17] 2010.500 2010.583 2010.667 > > ***********************First Time Through******************************* >> reFit <- nls(response ~ A + B * log(tsR - C), > start=c(A=10000,B=1350,C=2000)) > Error in numericDeriv(form[[3L]], names(ind), env) : > Missing value or an infinity produced when evaluating the model > In addition: Warning message: > In log(tsR - C) : NaNs produced > > ***********************Second Time Through******************************* >> reFit <- nls(response ~ A + B * > log(tsR-C),start=c(A=10078.4,B=1358.67,C=2009.07)) >> summary(reFit) > > Formula: response ~ A + B * log(tsR - C) > > Parameters: > Estimate Std. Error t value Pr(>|t|) > A 1.008e+04 1.427e+02 70.628 < 2e-16 *** > B 1.359e+03 2.997e+02 4.534 0.000339 *** > C 2.009e+03 7.314e-02 27468.499 < 2e-16 *** > --- > Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 > > Residual standard error: 388.8 on 16 degrees of freedom > > Number of iterations to convergence: 6 > Achieved convergence tolerance: 6.394e-06 > > [[alternative HTML version deleted]] > > > > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. -- Peter Dalgaard Center for Statistics, Copenhagen Business School Phone: (+45)38153501 Email: pd....@cbs.dk Priv: pda...@gmail.com ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
